BigQuery

Roiva writes these metric observations on each sync. Reference the key in a value formula to use this data in your ROI calculations.

Job Statistics

• Track how BigQuery compute consumption changes after introducing AI-driven data pipelines
• Measure query volume growth as a proxy for AI feature adoption
• Monitor bytes processed per month to understand infrastructure cost trends
• Use slot utilization as evidence of efficiency gains from automated query generation

1. In Google Cloud Console: Enable the BigQuery API on your project
2. In Google Cloud Console: Ensure your Google account has the BigQuery Job User or BigQuery Data Viewer role on the project
3. In Roiva: Click Connect — you will be redirected to Google to authorize
4. In Roiva: After authorizing, enter your GCP Project ID in the Project ID field and save
5. Back in Roiva: Link this connection to an initiative on the Initiatives tab

• The Project ID is the short identifier in your GCP console URL (e.g. my-gcp-project, not a numeric ID)
• INFORMATION_SCHEMA.JOBS requires your account to have BigQuery Job User role or equivalent — a read-only data viewer role is not sufficient
• If your BigQuery data lives in the EU multi-region, set Region to "eu" in the connection settings
• Data in INFORMATION_SCHEMA has up to a 24-hour delay for the most recent day